In the context of dimensionality reduction, PCA identifies directions that maximize what statistical property?

Variance

Principal Component Analysis (PCA) performs an orthogonal transformation to convert observations into a set of linearly uncorrelated variables called principal components. The first principal component accounts for as much of the variability in the data as possible.