Algorithmic error refers to mistakes or inaccuracies that occur in the output of an algorithm, which is a set of rules or instructions designed to solve a problem or perform a task. These errors can arise from various sources, including flawed data, incorrect coding, or unintended biases in the algorithm's design. Such errors can lead to significant consequences, especially in critical areas like finance, healthcare, and law enforcement. For instance, an algorithm used in predictive policing may unfairly target certain communities if it is based on biased historical data, highlighting the importance of careful algorithm development and testing.