A test dataset is a collection of data used to evaluate the performance of a machine learning model. It is separate from the training dataset, which is used to teach the model. By using a test dataset, researchers can assess how well the model generalizes to new, unseen data, ensuring it can make accurate predictions in real-world scenarios. Test datasets are crucial in the development of algorithms in fields like artificial intelligence and data science. They help identify any weaknesses in the model and guide improvements, ultimately leading to more reliable and effective applications in various industries.