Explainability (referring to a machine learning model) is the property of being explainable, interpretable, or understood -- to a human. The term is often used interchangeably with "interpretability". E.g. a linear regression is a very interpretable model because it is easy to understand how changes in input affect changes in output. Models that lack explainability are typically referred to as "black box".