In a nutshell
A random forest is an ensemble — a whole team of decision trees that vote. Each tree is trained on its own random sample of the data (bagging) and considers only a random subset of features at each split, which stops the trees from all making the same mistakes. For a new point, every tree predicts and the majority wins, giving an answer far steadier than any single tree.