It is a distance measure that best can be explained as the length of a segment connecting two points.
calculated from the cartesian coordinates of the points using the Pythagorean theorem
Euclidean distance is not scale in-variant which means that distances computed might be skewed depending on the units of the Features. Typically, one needs to normalize the data before using this distance measure.
Moreover, as the dimensionality increases of your data, the less useful Euclidean distance becomes. This has to do with the Curse Of Dimensionality
works great when you have low-dimensional data and the magnitude of the vectors is important to be measured