Machine learning is about making predictions from data.

This line is commonly used as a high-level, introductory description of what machine learning does: using observed data to build models that can forecast or infer outcomes on new inputs.

Machine learning’s core purpose is to learn patterns from examples so a system can generalize and produce useful outputs—often framed as predictions—when faced with unseen cases.