In the context of developing a machine learning model for a healthcare application, you are tasked with ensuring the model's predictions are fair and accurate across diverse patient populations. During the data preprocessing phase, you discover that the dataset predominantly includes records from urban hospitals, with minimal representation from rural areas. This scenario highlights a potential issue of data bias. Considering the implications of data bias on model performance and fairness, which of the following best describes data bias and its significance in machine learning? (Choose one correct option)