Random Forest is used for supervised learning tasks such as regression and classification. It is an ensemble technique that combines multiple decision trees to create a more accurate prediction model. It takes a subset of data and creates a multitude of decision trees. Each tree considers a random subset of the features, thus reducing the chances of overfitting and producing more accurate results.