What is the role of stochastic approximation in Random Forest convergence?

Random Forest can be viewed as a stochastic approximation of the regression function.

Each tree provides a noisy estimate of the true function. Averaging many such estimates forms a stochastic approximation that converges under decreasing variance assumptions. This links RF to Robbins-Monro style convergence frameworks.