Yunnan Province is a significant hub for inbound tourism in China, and exhibits a close correlation between inbound tourism and tourism-related carbon emissions. Consequently, exploring the interactions and influencing mechanisms between these two factors is of considerable importance. This paper analyzes the spatiotemporal evolution and differences in the coupling and coordinated development levels of inbound tourism and tourism carbon emissions in Yunnan Province. Utilizing the coupling coordination degree model and the Dagum Gini coefficient method, the study integrates the XGBoost model and random forest model to identify the primary influencing factors on the coupling and coordinated development of inbound tourism and tourism carbon emissions. Additionally, the Tobit model, random effects (RE) model, fixed effects (FE) model, and ordinary least squares (OLS) model are employed to analyze the bias effects of the relevant primary influencing factors. The results indicate that: (1) The level of coupling and coordinated development in Yunnan Province demonstrates a fluctuating yet upward trend; however, significant developmental disparities exist among regions, with a spatial evolution pattern observed as low (Nujiang) → high (Dali) → low (Chuxiong) → high (Kunming) → low (Qujing) from west to east. (2) The primary influencing factors for the coupling and coordinated development of inbound tourism and tourism carbon emissions in Yunnan Province include development factors, economic factors, population factors, and governance factors within the tourism industry. Among these factors, financial support for tourism exerts a significant negative impact on the coupling and coordinated development of inbound tourism and tourism-related carbon emissions. Conversely, the scale of tourism development, tourism infrastructure, economic development level, and the optimization of industrial structure positively influence this relationship. However, the effect of population agglomeration level is insignificant. Therefore, it is essential to actively promote the development of low-carbon tourism, optimize the tourism industrial structure, encourage large-scale operations, and foster coordinated development within the regional tourism sector. Additionally, optimizing the regional tourism industrial chain is crucial for achieving a high-level interaction between inbound tourism and tourism carbon emissions.