Since the 21st century, crisis events have been frequent and normalized globally, and improving resilience has become the key for the tourism industry to cope with various uncertainty risks. To reveal the reality of the economic resilience of tourism in China, this study employed the autoregressive integrated moving average model (ARIMA) to construct a counterfactual function and integrated with the peaks-over-threshold (POT) model and geographical detector model to evaluate the spatiotemporal evolution and influencing factors of the economic resilience of tourism in China from the resistance and recoverability perspective, with a view to providing a reference for consolidating the resilience of the economic system of tourism in China and promoting the sustainable development of its tourism economy. The results showed that the economic resilience of tourism in China can be divided into four types—robust, self-reliant, laissez-faire, and fragile—based on a baseline resistance of −0.361 and recoverability of 0.342. Under different contraction–recovery cycles, the resistance and recoverability of China’s tourism economy have been progressively improved, transforming from the centralized model to the discrete model, from a fragile to a self-reliant type. The type of economic resilience of tourism in China exhibited a clustered contiguous development trend, with obvious zonal distribution characteristics and self-reliant tourism economic resilience areas dominating, but most areas have not yet formed stable economic resilience in their tourism sector. The ecological environment quality, government management ability, and technological innovation level were the main factors affecting the economic resilience of tourism in China. The interactions between different influencing factors were more significant in strengthening the tourism economic resilience.