Machine learning is a branch of artificial intelligence (AI) that enables computers to learn patterns from data and use those patterns to make predictions, classifications, or recommendations. Instead of requiring a programmer to write an explicit rule for every possible situation, a machine learning system is trained using examples relevant to its task.

For example, imagine an email service that needs to identify unwanted messages. Developers can train a machine learning model using examples of spam and legitimate emails. During training, the model learns patterns that help distinguish between the two categories. When a new email arrives, the model can use what it learned to estimate whether the message is spam.

Machine learning does not mean that a computer thinks or understands everything like a human. A model learns statistical patterns from the data and training process used to develop it. Its results depend on factors such as data quality, model design, and how well it handles information it has not encountered before.

Machine learning is used in many fields, including healthcare, finance, transportation, education, cybersecurity, and online services. Different methods are suitable for different tasks, which is why understanding how machine learning works is a useful starting point for exploring modern AI technology.