Machine learning uses statistical learning to identify patterns in data and make predictions, such as distinguishing homes in New York from homes in San Francisco. A decision tree is a machine learning method that uses if-then statements to identify boundaries and define patterns in the data, but can overfit if it learns irrelevant details.