Model auditability refers to the ability to examine and evaluate the decision-making processes of a machine learning model to ensure transparency, accountability, and compliance with regulations. It enables stakeholders to understand, trust, and verify the model's outputs, which is essential for ethical and legal standards in AI deployment.