The Random Forest Algorithm is one of the most powerful and widely used supervised machine learning algorithms for classification and regression problems. It is an ensemble learning method, which means it combines multiple decision trees to produce more accurate, stable, and reliable predictions.In simple terms, Random Forest takes the wisdom of many “trees” to make smarter decisions — just like a group of experts making a judgment together.Random Forest is a collection of many Decision Trees working together. Each tree gives its own prediction, and the final result is decided by a majority vote (for classification) or an average (for regression).The idea is simple: instead of relying on one model (a single decision tree), Random Forest builds several models and combines them to get better performance and accuracy.