A tree ensemble is a collection of decision trees, where the output is the class selected by most trees. One of the weaknesses of using a single decision tree is the decision tree can be highly sensitive to small changes in the data. Ensembles are more robust and reduce this sensitivity, especially further down the tree as training data becomes smaller at each node.