  The OSIRIS-REx spacecraft encountered the asteroid (101955) Bennu on December
3, 2018, and has since acquired extensive data from the payload of scientific
instruments on board. In 2019, the OSIRIS-REx team selected primary and backup
sample collection sites, called Nightingale and Osprey, respectively. On
October 20, 2020, OSIRIS-REx successfully collected material from Nightingale.
In this work, we apply an unsupervised machine learning classification through
the K-Means algorithm to spectrophotometrically characterize the surface of
Bennu, and in particular Nightingale and Osprey. We first analyze a global
mosaic of Bennu, from which we find four clusters scattered across the surface,
reduced to three when we normalize the images at 550 nm. The three spectral
clusters are associated with boulders and show significant differences in
spectral slope and UV value. We do not see evidence of latitudinal
non-uniformity, which suggests that Bennu's surface is well-mixed. In our
higher-resolution analysis of the primary and backup sample sites, we find
three representative normalized clusters, confirming an inverse correlation
between reflectance and spectral slope (the darkest areas being the reddest
ones) and between b' normalized reflectance and slope. Nightingale and Osprey
are redder than the global surface of Bennu by more than $1\sigma$ from
average, consistent with previous findings, with Nightingale being the reddest
($S' = (- 0.3 \pm 1.0) \times 10^{- 3}$ percent per thousand angstroms). We see
hints of a weak absorption band at 550 nm at the candidate sample sites and
globally, which lends support to the proposed presence of magnetite on Bennu.
