Under the “dual-carbon” goals, the rapid development of new energy has led to a scarcity of rotational inertia, making inertia support from wind power systems increasingly important. However, providing inertia support by adjusting active power output reduces the economic efficiency of wind farms. To address this issue, a dynamic pricing and optimal allocation method for wind farm virtual inertia in the ancillary service market is proposed based on a Stackelberg game framework. First, the inertia support capability of wind farms is assessed based on rotor speed and power change constraints of wind turbines. The wind farm capacity is also evaluated, and a differentiated reward-penalty mechanism is established accordingly. Second, a Stackelberg leader-follower game model is constructed, where the power market operator acts as the leader and the wind farm cluster as followers. The market operator determines dynamic pricing and reward-penalty mechanisms to incentivize wind farms to participate in system inertia support. Finally, the proposed model and method are solved in MATLAB using the Gurobi commercial solver, and case studies verify their feasibility and effectiveness.