The Outlier Pattern addresses the challenge of handling data that deviates significantly from typical use cases, using a schema design approach that prevents outlier cases from dictating the overall application structure and reducing performance for standard operations. This pattern is particularly useful in scenarios where certain data items, such as a bestseller book or a large-scale video conference, exceed typical storage limits and require special handling. By flagging such outliers and managing their additional data separately, applications can maintain optimal performance for regular use cases while still accommodating exceptional ones. This approach leverages MongoDB's flexible data model and often involves extra code within the application to manage these outliers, which could necessitate additional maintenance. The pattern highlights the importance of balancing specific queries and common scenarios to ensure the application remains efficient and responsive, even when dealing with unexpected spikes in data load.