Outliers are unique points that are far away and abnormal compared to other data points. Sometimes, outliers are considered noise, while in some cases, they are considered to be valuable sources of information. Outliers can be detected by using the clustering technique. The points far away from all the clusters can be called outliers. Plotting techniques like box plots, scatter plots, and histograms can be used for outlier detection. Supervised methods can be used, e.g., modelling to find the normal objects and considering those points that don't fit in this model as outliers. Statistical approaches based on distance and mathematical functions also help in detecting outliers.