An inlier is a data point that lies at the same level as the rest of the dataset. Finding an inlier in the dataset is difficult when compared to an outlier as it requires external data to do so. Inliers, similar to outliers reduce model accuracy. Hence, even they are removed when they’re found in the data. This is done mainly to maintain model accuracy at all times.
