Random forests are supervised machine learning method for classification and regression.
Random forest is way of averaging multiple decision trees which are trained on different parts of the same training set.
In Decision tree we make splits on predictor variables to predict the target.
In Random Forest,we build many decision trees and then take the opinion of all the decision tree to predict the outcome variable.
If you want to learn about Random Forest paramters used in fitting the model in R, then please have a look on the video