In this work, the potential of cryogen-free low-field ¹H-NMR spectroscopy combined with chemometrics was examined to authenticate honeys based on their botanical origin and to determine the presence and content of low-priced sugar syrups in genuine honeys. The multivariate classification data algorithms of PCA, HCA and SIMCA were constructed over the integrated data of benchtop NMR spectroscopy, by using 95 genuine honey samples from 15 different types of monofloral, polyfloral and honeydew honeys. The supervised PLS-R models were also constructed to identify quantitative detection limits for the cheap sugar syrups in adulterated honey–sugar syrup sample sets. The monofloral honeys were especially forecasted with an accuracy of 100% by the SIMCA model, and they offered a distinct demarcation of the honeys and were employed to classify honeys. The minimum detection limits for syrup adulterants were 0.96% in monofloral honeys, 1.55% in polyfloral honeys and 1.93% in honeydew honeys, respectively, with high R² values (> 0.9970). It is concluded that the profiles of major carbohydrate molecules and minor components by low-field ¹H-NMR spectroscopy with chemometrics could be a powerful and potential device for the demarcation of honeys from diverse botanical origins and the quantification of low-priced sugar syrups in pure honeys.