Random forest is a popular machine learning algorithm that is used for both classification and regression tasks. It is an ensemble method that involves creating multiple decision trees during the training phase, and then averaging their predictions to make a final prediction. Random forest is known for its high accuracy, robustness against overfitting, and ability to handle large datasets with high dimensionality. It is a versatile algorithm that can be applied to a wide range of problems in various fields, such as finance, healthcare, and marketing.