Machine learning models adapt over time with new data through a process known as retraining. This involves continuously updating the model using fresh datasets to enhance its accuracy and performance. By integrating new information, the models can recognize evolving patterns and trends, thus improving predictions. Regularly updating ensures the model remains relevant and responsive to changes in the underlying data environment, ultimately benefiting applications in fields such as finance and healthcare.