Algorithmic fairness refers to the principle that algorithms, especially those used in decision-making processes, should operate without bias against any individual or group. This means that the outcomes produced by these algorithms should be equitable and just, ensuring that no particular demographic is unfairly disadvantaged. To achieve algorithmic fairness, developers often employ various techniques to identify and mitigate biases in data and algorithms. This includes analyzing datasets for discrimination and adjusting algorithms to promote equity across different populations. The goal is to create systems that are transparent and accountable, fostering trust in automated decisions.