The explanation of the identified outliers is frequently provided to the users when other techniques are used to detect the outliers that are suggested in the study. This situation is quite challenging for the users to take the relevant actions that are regarded with the identified outliers as the outcome. If the outliers are detected, then the explanations need to be provided with outliers to reduce the challenge. Some surveys are available for the outlier interpretation, and some surveys are available to detect an outlier. The survey presents an outlier interpretation in the proposed system where useful knowledge is obtained from anomalous data to fill the gap and describe the data. The types of outlier explanations are defined, and the difficulties are discussed while creating every type. The existing outlier interpretation approaches are reviewed, and the processes of mentioning the difficulties are discussed. The applications of outlier interpretation are discussed, and the existing techniques are utilised for the determination of outlier explanations are reviewed. Further, the possible future research ways are discussed.