What characterizes 'machine learning'?

Machine learning is characterized as a subset of artificial intelligence that enables systems to learn and improve from experience without explicit programming. This essential trait highlights how machine learning algorithms can adapt and optimize their performance based on the data they process, allowing them to make predictions or decisions without needing to be explicitly instructed on how to perform the task.

The emphasis on "learning from experience" means that as machine learning models are exposed to more data, they can refine their operations and improve their accuracy over time. This adaptive capability is what distinguishes machine learning from traditional programming approaches, where a developer would need to write specific rules for every possible situation. By utilizing patterns and insights derived from large datasets, machine learning systems can generalize their knowledge to new, unseen data, making them powerful tools in various applications, from image recognition to natural language processing.