Random forests is another ensemble learning model. Here, we get all the ensemble learning objects from the ensemble submodule in scikit-learn. For example, here, we use the RandomForestRegressor method. The following screenshot, shows the algorithm used for this model:
So, in a case where we produce a forest of 50 individual predictors, this algorithm will produce 50 individual trees. Each tree will have max_depth of 16, which will then produce the individual predictions again by majority vote.