In machine learning, an Attribute (or feature) is a measurable property of an instance within a dataset. Attributes can be numerical (e.g., height, temperature), categorical (e.g., gender, color), or ordinal (e.g., ranking levels). Attributes define the input variables that models use to learn patterns and make predictions. Feature engineering techniques enhance attributes by transforming raw data into more informative representations.