In the context of machine learning project development for a telecommunications company aiming to predict customer churn, the team is equipped with a large dataset. Despite the dataset's size, the team is apprehensive about the model's efficacy on new, unseen data due to potential pitfalls in the dataset's composition or model's design. Considering the importance of dataset representativeness and model generalizability, which of the following scenarios most accurately illustrates a common pitfall that could lead to underperformance of the model on new, unseen data? (Choose one correct option)