Temporal resolution in a spectrogram is fundamentally determined by the window size, equal to the FFT-length. In a simple plot of the spectrogram of a short signal, one pixel on the screen equals one window. If a high frequency resolution is wanted, which requires long windows, the spectrogram appears pixelated on the time axis. This can be smoothed by making windows overlap. 50% overlap gives twice the display resolution, 90% overlap 10 times the display resolution, which creates visually more appealing displays. When interpreting the spectrogram, this "smoothing" must be kept in mind, as the fundamental time resolution is still given by the FFT-size/window length and cannot be improved by overlapping. Windows are correlated, as explained in @WMXZ's answer.
If a Hann window is used, one can argue that 50% overlap is well justified, because no part of the signal contributes more to the spectrogram than others. In the individual Hann-window, the middle part is weighted with 100%, but the beginning and end are weighted 0%. However, the sum of a series of 50% overlapping Hann-windows equals 1 except for the first half and last half window, meaning that every part of the signal contributes equally. If larger overlap is used, the overlapping segments contribute with more than 100%, and less than 100% for smaller overlaps.
Same argument can be used for overlapping windows in power spectrum estimates.
This symmetry a particularly useful feature of Hann windows, generally not true for other windows (Bartlett/triangular window is one exception), making Hann-windows a very good first choice for analysis.