Which statement best describes Machine Learning (ML)?

The statement that best describes Machine Learning (ML) is that these systems learn from data and enhance their performance. Machine Learning relies on algorithms that process large amounts of data to identify patterns and make decisions based on that data, rather than strictly adhering to predefined rules. This ability to improve over time through exposure to more data distinguishes ML from traditional programming approaches, which typically rely on explicit instructions given by a programmer.

In contrast, systems that operate only on predefined rules lack the flexibility and adaptability that ML systems exhibit. While some ML systems may exhibit human-like problem-solving capabilities in specific tasks, they do not completely mimic human thought processes, which involve complex emotions, reasoning, and intuition. Additionally, while some machine learning systems may require human supervision, especially during the training phase, they are designed to operate with increasing autonomy as they learn from data. Therefore, the statement highlighting learning from data and performance enhancement accurately captures the essence of what Machine Learning encompasses.