Clarification on K Means Clustering Algorithm and its Analysis
K-means is an iterative algorithm. So what you have in the picture may be one of the early iterations and therefore the sum of squared distances (between points and clusters) has not been minimised yet. In further iterations, the circled point would indeed be assigned to cluster centroid C1.

Now, having said that, and this is purely speculation, but if the diagram in your picture is not simply 2 dimensional as we interpret it to be, but is actually a 2-d projection from a higher dimensional feature space, then indeed the circled point may be closer to centroid C2 in that higher dimensional space (although it doesn’t look like it in 2-d).