A Decision Tree is a machine learning architecture consisting of decision nodes that progressively 'narrow down' the value to be assigned to an input. Each node implements a test to decide, based on certain features, which branch to follow. The process stops when a leaf node is reached, at which point the values of the training samples corresponding to that node are used to compute the output.